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Automated Detection of Low-Contrast Solar Features Using the Phase-Congruency Algorithm |
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| Authors: | Song Feng Zhi Xu Feng Wang Hui Deng Yunfei Yang Kaifan Ji |
| Institution: | 1. Yunnan Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China 2. Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100012, China 3. Key Laboratory of Modern Astronomy and Astrophysics, Nanjing University, Ministry of Education, Nanjing, 210093, China 4. Yunnan Astronomical Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Kunming, 650011, China |
| Abstract: | We propose a new feature-detection technique based on phase-congruency (PC) measurements to automatically recognize or enhance faint features in solar observations, such as off-limb coronal loops and umbral dots. Compared with other feature-detection methods that are based on gradient illuminance and imaging filtering, PC-based measurements are particular efficient for recognizing faint features, which generally have a low-intensity contrast to their surroundings. In the present article, we carry out a PC-based measurement of the local weighted mean phase angle (LWMPA) at each point in an image to indicate or highlight low-contrast features. We first used artificial images to check the detection accuracy and sensitivity to the noise of this approach. Subsequently, we applied this approach to an EUV observation obtained by the Solar Dynamics Observatory/Atmospheric Imaging Assembly to highlight off-limb coronal loops, and a photospheric observation obtained by the Hinode/Solar Optical Telescope to recognize faint dots within the cores of sunspots and pores. The results illustrate that this PC-based measurement of the LWMPA is a robust detection method for faint structures in solar observations. |
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